A decision support system (DSS) is a computer-based information system that supports business or organizational decision-making activities. DSSs serve the management, operations, and planning levels of an organization and help to make decisions, which may be rapidly changing and not easily specified in advance.
DSSs include knowledge-based systems. A properly designed DSS is an interactive software-based system intended to help decision makers compile useful information from a combination of raw data, documents, personal knowledge, or business models to identify and solve problems and make decisions. Three fundamental components of a DSS architecture are;                1. the database (or knowledge base);        2. the model (i.e., the decision context and user criteria);        3. the user interface.        
DSS architectures are disclosed in the following publications:                George. M. Marakas. Decision support systems in the 21st century. In Prentice Hall; US ed edition (Nov. 3, 1998), 1998.        D. J. Power. Decision support systems: concepts and resources for managers. In Westport, Conn., Quorum Books, 2002.        R. H. Sprague and E. D. Carlson. Building effective decision support systems. In Englewood Clis, N.J., Prentice-Hall. ISBN 0-130-86215-0, 1982.        Haag Stephen, Cummings Maeve, and McCubbrey Donald. Management information systems: For the information age. In McGraw-Hill Companies, 2003.        
The users themselves are also important components of the architecture.
There are several ways to classify DSS applications. Not every DSS fits neatly into one category, but may be a mix of two or more architectures.
Holsapple and Whinston (Clyde W. Holsapple and Andrew B. Whinston. Decision support systems: A knowledge-based approach. In West Group; 10th edition. ISBN 0-324 03578-0, 1996) classify DSS into the following six frameworks: Text-oriented DSS, Database-oriented DSS, Spreadsheet-oriented DSS, Solver-oriented DSS, Rule-oriented DSS, and Compound DSS.
A compound DSS is the most popular classification for a DSS. It is a hybrid system that includes two or more of the five basic structures described by Holsapple and Whinston.
The support given by DSS can be separated into three distinct, interrelated categories: Personal Support, Group Support, and Organizational Support (R. D. Hackathorn and P. G. W. Keen. Organizational strategies for personal computing in decision support systems. MIS Quarterly, 5(3), 1981).
DSS components may be classified as:                1. Inputs: Factors, numbers, and characteristics to analyze;        2. User Knowledge and Expertise: inputs requiring manual analysis by the user;        3. Outputs: Transformed data from which DSS “decisions” are generated;        4. Decisions: Results generated by the DSS based on user criteria.        
DSSs which perform selected cognitive decision-making functions and are based on artificial intelligence or intelligent agents technologies are called Intelligent Decision Support Systems (IDSS). Flexible manufacturing systems (FMS) (Felix Chang, Bong Jiang, and Nelson Tang. The development of intelligent decision support tools to aid the design of flexible manufacturing systems. International Journal of Production Economics, 65:73-84, 2000) and medical diagnosis systems (D. Walker. Similarity determination and case retrieval in an intelligent decision support system for diabetes management. In MSc Thesis, Ohio University, Computer Science—Engineering, 2007) can also be considered examples of intelligent decision support systems. Many IDSS implementations are based on expert systems, a well established type of KBS that encode the cognitive behaviours of human experts using predicate logic rules and have been shown to perform better than the original human experts in some circumstances (J. Baron. Thinking and deciding. In Cambridge University Press. 1998/E. Turban E., L. VoIonio L., E. McLean, and J. Wetherbe. Information technology for management. In Wiley, 2009).